Clove plant have high economic value and one of many export commodity of Indonesian plantation product, in Wonosalam region Jombang Regency there are less well groomed clove farm because the owners are not at all the times in the farm, and thus the plant susceptible to disease and reduced yields from the clove harvest. Needed a way to help farmers to know the types of diseases that attack the clove plants, then made a clove plant diagnosis system using the algorithm Modified K - Nearest Neighbor (MKNN). The diagnostic system will provide clove plant disease information based on inputs of observable symptoms of the plant. MKNN algorithm is the development of KNN algorithm by adding calculation process of data training validation and weight voting. Validation calculation aims to overcome the problem of data that deviates on the KNN algorithm in order to avoid bias and weight voting aims to calculate the weight of the data. Accuracy of clove plant diagnosis system using MKNN algorithm is 96.67%.
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